new cran update with small fixes

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: ENMeval
 Type: Package
 Title: Automated Runs and Evaluations of Ecological Niche Models
-Version: 0.3.0
-Date: 2018-07-23
+Version: 0.3.1
+Date: 2020-09-08
 Author: Robert Muscarella, Peter J. Galante, Mariano Soley-Guardia, Robert A. Boria, Jamie M. Kass, Maria Uriarte and Robert P. Anderson
 Maintainer: Robert Muscarella <[email protected]>
 Description: Automatically partitions data into evaluation bins, executes ecological niche models across a range of settings, and calculates a variety of evaluation statistics.  Current version only implements ENMs with Maxent (Phillips et al. 2006) or maxnet (Phillips et al. 2017).
@@ -26,4 +26,4 @@ Suggests: rJava (>= 0.5-0),
 	rgeos,
 	sp
 VignetteBuilder: knitr
-RoxygenNote: 6.0.1
+RoxygenNote: 7.1.1

NEWS

@@ -1,3 +1,8 @@
+ENMeval 0.3.1
+===========
+o  Vignette no longer uses spocc to download occurrences due to intermittent problems downloading from GBIF. This data is now loaded from a RDS file.
+
+
 ENMeval 0.3.0
 ===========
 o  Changed the default behavior to use the 'maxnet' function of the 'maxnet' package instead of the 'maxent.jar' program, and removed the dependency on the 'rJava' package by default, among others.

man/ENMeval-package.Rd

@@ -8,8 +8,8 @@
 \tabular{ll}{
 Package: \tab ENMeval\cr
 Type: \tab Package\cr
-Version: \tab 0.3.0\cr
-Date: \tab 2018-07-23\cr
+Version: \tab 0.3.1\cr
+Date: \tab 2020-09-08\cr
 License: \tab GNU 3.0\cr
 }
 

man/ENMevaluate.Rd

@@ -188,7 +188,8 @@ occ <- cbind(x,y)
 
 \dontrun{
 ### This call gives the results loaded below
-enmeval_results <- ENMevaluate(occ, env, method="block", n.bg=500, categoricals=4, algorithm='maxent.jar')
+enmeval_results <- ENMevaluate(occ, env, method="block", n.bg=500, 
+  categoricals=4, algorithm='maxent.jar')
 }
 
 data(enmeval_results)

man/enmeval_results.Rd

@@ -51,7 +51,8 @@ occ <- cbind(x,y)
 
 \dontrun{
 ### This gives the results that are loaded below:
-enmeval_results <- ENMevaluate(occ, env, method="block", n.bg=500, categoricals=4, algorithm='maxent.jar')
+enmeval_results <- ENMevaluate(occ, env, method="block", n.bg=500, 
+  categoricals=4, algorithm='maxent.jar')
 }
 
 data(enmeval_results)